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Discriminative FaceTopics for face recognition via latent Dirichlet allocation
T.I. Dhamecha, P. Sharma, ,
Published in Institute of Electrical and Electronics Engineers Inc.
2016
Pages: 1 - 8
Abstract
Latent Dirichlet Allocation is a widely used approach for topic modeling and it has been successfully applied in several information retrieval applications. In this paper, we introduce this modeling technique for face recognition, by making an analogy between the two domains. We utilize latent Dirichlet allocation to represent facial regions in terms of FaceTopics. Further, linear discriminant analysis is utilized to obtain discriminative FaceTopics which are more suitable for classification tasks. The performance of the proposed approach is evaluated on the CMU-MultiPIE dataset under illumination and expression variations. The evaluation on over more than 50k images shows the effectiveness of the proposed approach. Further, the proposed approach shows improved identification results on e-PRIP dataset for matching composite sketches to photos. © 2016 IEEE.
About the journal
JournalData powered by Typeset2016 IEEE Winter Conference on Applications of Computer Vision, WACV 2016
PublisherData powered by TypesetInstitute of Electrical and Electronics Engineers Inc.
Open AccessNo